Abstract
The search for low autocorrelated binary sequences(LABS) is a combinatorial optimization problem, which is NP-hard. In this paper, we apply Greedy Randomized Adaptive Search Procedures (GRASP) to tackle the LABS problem. The algorithm is capable of systematically recovering best-known solutions reported by now. Furthermore, it can find out good autocorrelated binary sequences sequences in considerably less time as comparison with other heuristic methods.
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Wang, H., Wang, S. (2010). GRASP for Low Autocorrelated Binary Sequences. In: Huang, DS., Zhao, Z., Bevilacqua, V., Figueroa, J.C. (eds) Advanced Intelligent Computing Theories and Applications. ICIC 2010. Lecture Notes in Computer Science, vol 6215. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14922-1_32
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DOI: https://doi.org/10.1007/978-3-642-14922-1_32
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-14921-4
Online ISBN: 978-3-642-14922-1
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